Transfer Function-Guided Saliency-Aware Compression for Transmitting Volumetric Data

We introduce a transfer-function-guided three-dimensional (3-D) block-based saliency-aware compression scheme for volumetric data that is both content and spatially scalable. Salient 3-D volumetric blocks are identified and weighted with the help of a transfer function which is used to render the da...

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Bibliographic Details
Published in:IEEE transactions on multimedia Vol. 22; no. 9; pp. 2262 - 2277
Main Authors: Park, Ji Hwan, Gutenko, Ievgeniia, Kaufman, Arie E.
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.09.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Compression
Compression tests
Data compression
Data visualization
discrete cosine transform
Discrete cosine transforms
Electronic devices
Encoding
Error reduction
Image coding
Image reconstruction
Mobile computing
Progressive image transmission
Rendering (computer graphics)
Salience
saliency
Three-dimensional displays
Transfer functions
volume visualization
Wavelet transforms
wavelets
ISSN:1520-9210, 1941-0077
Online Access:Get full text
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Summary:We introduce a transfer-function-guided three-dimensional (3-D) block-based saliency-aware compression scheme for volumetric data that is both content and spatially scalable. Salient 3-D volumetric blocks are identified and weighted with the help of a transfer function which is used to render the data. We describe our method in the form of a framework for processing, progressive transmission, and visualization of volumetric data on a target device, such as a mobile device with limited computational resources. In particular, we address the transmission bottleneck incurred when transferring 3-D volumetric data. Identified salient regions are progressively transmitted to the target device. The received data are rendered progressively in the respective order with a predefined or user-defined transfer function. Our method is developed with medical applications in mind, where preservation of all information is essential for clinical diagnosis. Because our method is integrated into a resolution scalable coding scheme with an integer wavelet transform of the image, it allows the rendering of each significant region at a different resolution up to fully lossless reconstruction. We perform a thorough qualitative and quantitative evaluation of the saliency detection method and the resulting saliency-aware compression schemes. Our results show reduced error in representation of the volumetric data with our method.
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ISSN:1520-9210
1941-0077
DOI:10.1109/TMM.2017.2757759